Third generation cellular communications employ wideband CDMA (WCDMA). CDMA is a method for transmitting simultaneous signals over a shared portion of the spectrum. CDMA spreads the signal over the full bandwidth of the CDMA frequency band using a spreading code that, because it is orthogonal to all the other spreading codes used, allows each modulated bit stream to be distinguished (decoded) at the receiver from all of the other signals and noise. The rate of the spreading signal is known as the “chip rate,” as each bit in the spreading signal is called a “chip”, e.g., one bit from the modulated bit stream is spread into 128 chips, giving the receiver an enormous amount of data it can average to determine the value of one bit.
A Rake receiver structure is commonly used to recover information corresponding to one of the user data streams in CDMA receivers. In a typical Rake receiver, a received composite signal is correlated with a particular spreading sequence assigned to the receiver to produce a plurality of time-offset correlations, each one corresponding to an echo or image of a transmitted spread spectrum signal. The correlations are then combined in a weighted fashion, i.e., respective correlations are multiplied by respective weighting factors and then summed to produce transmitted symbol estimates that hopefully correspond to the originally transmitted symbols.
WCDMA has been evolving to support higher data rates over the radio interface. In the downlink from the radio access network to the mobile terminal, high speed downlink (base station-to-mobile station) packet access (HSDPA) may use multi-code transmission (i.e., more than one spreading code is used to send the information bit stream) and/or higher-order modulation to send more modem (modulated) bits per frame, thereby enabling higher rates. A major obstacle to achieving higher bit rates relates to the dispersive characteristics of a radio channel. If the channel is dispersive, self-interference results primarily due to loss of orthogonality between the multi-code signals. This form of self-interference is referred to as intercode interference (ICI). Another form of self-interference is interference from successive symbols on the same code. This interference is referred to as intersymbol interference (ISI). Higher-order modulation is particularly sensitive to self-interference. The story is similar in the uplink (mobile to base station). The “enhanced uplink” currently being standardized for WCDMA will use multi-code and low spreading factor to enable higher rates. At high rates, dispersion leads to significant self-interference.
FIG. 1 helps illustrate the self-interference problem. In this simple example, three symbols 1, 2, and 3 are sent sequentially on one spreading code while three other symbols 4, 5, and 6 are sent sequentially on a different spreading code. As a result, two symbols are sent in parallel during each symbol period. Due to time dispersion, the transmitted signal travels along two paths such that the second path has a longer delay than the first. As a result, the receiver receives two overlapping signal images corresponding to the two different path delays. Assume recovery of the image of symbol 2 (the symbol of interest) from the first path (identified with dots). While this symbol 2 image overlaps with the image of symbol 5 on path 1, there is no interference between these two images because spreading codes 1 and 2 are orthogonal and their correlation is substantially zero. But there is interference from path 2. Specifically, there is ISI from symbol 1 on the same code (shown with slanted lines) and ICI from symbols 4 and 5 (shown with horizontal lines). The overlapping portion of symbol 1 path 2 interferes when symbol 2 path 1 is despread. Overlapping portions of symbols 4 and 5 in path 2 are not aligned with symbol 2 path 1, so the desired orthogonality is lost.
There are different approaches to this self-interference problem. One is linear equalization to suppress self-interference. One linear equalization approach is to perform equalization despreading as part of Rake combining process using a generalized-Rake (G-Rake) receiver. Combining weights (vector w) are determined by net channel estimates (vector h) and an impairment covariance matrix estimate (R) by solvingRw=h.  (1)With code-specific G-Rake, the impairment covariance and/or the channel estimates can be determined based on a set of spreading sequences being used. Another linear equalization approach is chip equalization where chip samples are filtered prior to despreading to suppress interference. The main limitation with linear equalization is the limited amount of interference suppression. Loss of orthogonality is due to the channel. Linear equalizers try to undo the channel to restore orthogonality. But this enhances noise and other forms of interference. Thus, this trade-off prevents full restoration of orthogonality.
With nonlinear equalization, such as maximum likelihood sequence estimation (MLSE) and maximum a-posteriori probability (MAP) equalization, self interfering symbols are jointly detected. Thus, rather than undoing the channel, the receiver accounts for what the channel did to the signal. This avoids the noise enhancement problem. The drawback is much higher complexity relative to linear equalization. The receiver must maintain a state space whose size depends exponentially on how many symbols interfere with one another.
In CDMA system, interference cancellation has been proposed for improved demodulation. Modem symbols are detected and then used to remove their contribution to the received signal so that detection of other symbols is improved. But modem symbol detection is not always accurate. Thus, interference cancellation can actually worsen the situation when symbol detection errors are made. Also, such an approach does not utilize forward error correction (FEC) coding structure to obtain reliable modem symbol estimates.
Turbo-equalization is an approach in which equalization and FEC decoding are performed iteratively, each exchanging information with the other. It was originally developed for narrowband or nonspread systems and later applied to CDMA systems, primarily in conjunction with nonlinear equalization. Again, the problem is complexity. To reduce complexity in turbo-equalization, a linear equalizer can be used that performs chip-level equalization. A drawback with chip equalization is that it is complicated; it is easier to equalize the despread signal. Moreover, traditional CDMA receiver architectures initially despread the received signal and perform linear equalization after despreading.